--- description: How to make 3D Isosurface Plots in Python with Plotly. display_as: 3d_charts has_thumbnail: True ipynb: ~notebook_demo/272 language: python layout: user-guide name: 3D Isosurface Plots order: 12.1 page_type: u-guide permalink: python/3d-isosurface-plots/ redirect_from: python/isosurfaces-with-marching-cubes/ thumbnail: thumbnail/isosurface.jpg title: Python 3D Isosurface Plots | plotly --- {% raw %}
With go.Isosurface, you can plot isosurface contours of a scalar field value, which is defined on x, y and z coordinates.
In this first example, we plot the isocontours of values isomin=2 and isomax=6. In addition, portions of the sides of the coordinate domains for which the value is between isomin and isomax (named the caps) are colored. Please rotate the figure to visualize both the internal surfaces and the caps surfaces on the sides.
import plotly.graph_objects as go
fig= go.Figure(data=go.Isosurface(
x=[0,0,0,0,1,1,1,1],
y=[1,0,1,0,1,0,1,0],
z=[1,1,0,0,1,1,0,0],
value=[1,2,3,4,5,6,7,8],
isomin=2,
isomax=6,
))
fig.show()
For a clearer visualization of internal surfaces, it is possible to remove the caps (color-coded surfaces on the sides of the visualization domain). Caps are visible by default.
import plotly.graph_objects as go
import numpy as np
X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2
fig = go.Figure(data=go.Isosurface(
x=X.flatten(),
y=Y.flatten(),
z=Z.flatten(),
value=values.flatten(),
isomin=10,
isomax=40,
caps=dict(x_show=False, y_show=False)
))
fig.show()
import plotly.graph_objects as go
import numpy as np
X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2
fig = go.Figure(data=go.Isosurface(
x=X.flatten(),
y=Y.flatten(),
z=Z.flatten(),
value=values.flatten(),
isomin=10,
isomax=50,
surface_count=5, # number of isosurfaces, 2 by default: only min and max
colorbar_nticks=5, # colorbar ticks correspond to isosurface values
caps=dict(x_show=False, y_show=False)
))
fig.show()
import plotly.graph_objects as go
import numpy as np
X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2
fig = go.Figure(data=go.Isosurface(
x=X.flatten(),
y=Y.flatten(),
z=Z.flatten(),
value=values.flatten(),
opacity=0.6,
isomin=10,
isomax=50,
surface_count=3,
caps=dict(x_show=False, y_show=False)
))
fig.show()
Here we visualize slices parallel to the axes on top of isosurfaces. For a clearer visualization, the fill ratio of isosurfaces is decreased below 1 (completely filled).
import plotly.graph_objects as go
import numpy as np
X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2
fig = go.Figure(data=go.Isosurface(
x=X.flatten(),
y=Y.flatten(),
z=Z.flatten(),
value=values.flatten(),
isomin=5,
isomax=50,
surface_fill=0.4,
caps=dict(x_show=False, y_show=False),
slices_z=dict(show=True, locations=[-1, -3,]),
slices_y=dict(show=True, locations=[0]),
))
fig.show()
import plotly.graph_objects as go
import numpy as np
X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, 0:5:20j]
values = X * X * 0.5 + Y * Y + Z * Z * 2
fig = go.Figure(data=go.Isosurface(
x=X.flatten(),
y=Y.flatten(),
z=Z.flatten(),
value=values.flatten(),
isomin=30,
isomax=50,
surface=dict(count=3, fill=0.7, pattern='odd'),
caps=dict(x_show=True, y_show=True),
))
fig.show()
import plotly.graph_objects as go
import numpy as np
X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, -5:5:40j]
# ellipsoid
values = X * X * 0.5 + Y * Y + Z * Z * 2
fig = go.Figure(data=go.Isosurface(
x=X.flatten(),
y=Y.flatten(),
z=Z.flatten(),
value=values.flatten(),
colorscale='BlueRed',
isomin=10,
isomax=50,
surface_count=3,
caps=dict(x_show=False, y_show=False)
))
fig.show()
import plotly.graph_objects as go
import numpy as np
X, Y, Z = np.mgrid[-5:5:40j, -5:5:40j, 0:5:20j]
values = X * X * 0.5 + Y * Y + Z * Z * 2
fig = go.Figure(data=go.Isosurface(
x=X.flatten(),
y=Y.flatten(),
z=Z.flatten(),
value=values.flatten(),
isomin=30,
isomax=50,
surface=dict(count=3, fill=0.7, pattern='odd'),
showscale=False, # remove colorbar
caps=dict(x_show=True, y_show=True),
))
fig.update_layout(
margin=dict(t=0, l=0, b=0), # tight layout
scene_camera_eye=dict(x=1.86, y=0.61, z=0.98))
fig.show()
See https://plot.ly/python/reference/#isosurface for more information and chart attribute options!